Smart Devices Reveal Lots of Detail About Obvious Truths

The Internet of Things and Big Data analytics promise to shine a light into dark corners of ignorance about human behavior, places where most of us don’t even suspect corners exist.

However original or unsuspected the results, however, it turns out that having a really smart way to get a better answer to a particular problem doesn’t the answer itself any more valuable. Researchers at MIT’s Newman Laboratory for Biomechanics and Human Rehabilitation, for example, have built a semi-autonomous, artificial-intelligence-imbued robotic device whose job it is to determine whether the wearer’s ankle is stiff.

The machine, named “Ankelbot,” attaches to a knee brace and a custom-designed shoe with which it moves the wearer’s foot along a specific trajectory, bending in different directions to calculate whether the joint is stiff or not.

“Imagine you have a collection of pebbles, and you wrap a whole bunch of elastic bands around them,” lead researcher Neville Hogan, the Sun Jae Professor of Mechanical Engineering at MIT, wrote in the announcement of Anklebot’s existence. “That’s pretty much a description of what the ankle is. It’s nowhere near a simple joint from a kinematics standpoint.”

Ankles are strongest when moving the foot up and down, and weaker when moving from side to side, though it turns out the mechanism the ankle uses to move side-to-side is independent of the one it uses to move up and down: a finding that might help physiologists better understand the ankle’s dynamic characteristics as well as its physical properties, Hogan added. Even without previously unsuspected revelations, Anklebot data should help physical therapists and trainers create more effective recovery or rehabilitation plans, Hogan said.

Distraction

Outside the physiological realm, datasets derived from devices are offering a whole new window into human behavior.

A carefully quantitative survey of 777 students at six universities has confirmed the obvious: college students are distracted in class by Facebook and texting with friends.

The survey rated different sites and devices according to how often or effectively they distracted students. Students surveyed during the Fall of 2012 admitted their digital devices distracted them during class, but the numbers were lower than expected, following studies such as one from Experian Marketing Services that estimated 18- to 24-year-olds receive an average of 3,853 text messages per month.

Thirty-five percent said they were distracted one to three times per day; 27 percent admitted four to 10 times per day; 16 percent admitted being distracted 11 to 30 times per day and only 15 percent admitted more than 30 distractions per day.

Only eight percent said they were never distracted; fewer than 17 percent said the devices themselves are not a distraction. (Full paper available here.)

Of those that were distracted, 86 percent admitted texting; 68 percent admitted checking email; 66 percent said they used social networks; 38 percent surfed the web and 8 percent played games.

Students admitted distraction might be a problem, but 91 percent opposed banning devices in class; 72 percent preferred a policy that would impose fines or other penalties for violating a no-distraction policy, but wanted a first warning to soften the blow when they did it anyway.

People, even students, wouldn’t spend that much time on their digital devices if the technology didn’t make them more productive in some way, however, if the justifications for BYOD programs in most large companies can be believed.